Triple
T6251455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Memphis in May International Festival events |
E140053
|
entity |
| Predicate | barbecueContestLevel |
P746
|
FINISHED |
| Object | international |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: international | Statement: [Memphis in May International Festival events, barbecueContestLevel, international]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: barbecueContestLevel Context triple: [Memphis in May International Festival events, barbecueContestLevel, international]
-
A.
hasSpiciness
Indicates that one entity possesses a certain level or quality of spiciness in relation to another entity or a defined scale.
-
B.
grillFuel
Indicates that a specified fuel source is used to power or operate a grill.
-
C.
competitionLevel
chosen
Indicates the degree or intensity of competitive pressure or rivalry present in a given context or interaction.
-
D.
hasCookingQuality
Indicates that something possesses a particular characteristic or attribute related to cooking, such as flavor, texture, or suitability for a cooking method.
-
E.
hasBitternessLevel
Indicates that an entity is associated with a specific degree or intensity of bitterness.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c008b4858c819095b0199114a9a87b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0633fb2ac8190b71b8e35fa923300 |
completed | March 22, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69c056037bf88190a0a3fe7429345d0b |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:24 p.m.